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@tinoeberl@mastodon.online
2026-02-03 15:16:57

#Firefox führt ab Version 148 eine neue Einstellung ein, mit der Nutzer alle aktuellen und zukünftigen generativen #AI-Funktionen im Browser blockieren können.
Alternativ lassen sich einzelne Features wie #Übersetzungen

@kubikpixel@chaos.social
2025-12-31 08:35:13

»Exploring alternatives to UUIDv4; Enter ULIDs.
UUIDv4 is a commonly used unique identifier format. UUIDv4 is a standardized format for generating unique identifiers that are widely used in distributed systems. […]«
Of course, UUID is usually used as a clear data hint and there are countless alternatives that are optimal depending on their application but I didn't know ksuid yet.
👤

@Techmeme@techhub.social
2026-01-28 12:35:57

Some US college students say they are using AI "humanizer" tools to alter text to avoid cheating accusations; AI detection tools now aim to catch "humanizers" (Tyler Kingkade/NBC News)
nbcnews.com/tech/internet/coll

@DieGesellschafterinLang@swiss.social
2025-11-27 04:53:21

"Ab einem gewissen Alter sind viele Menschen, die man kannte, verstorben und können einen nicht mehr verklagen."
Lesenswertes Interview mit der Schriftstellerin Margaret Atwood (86). Neues Buch: "Book of Lives"
#Alter #Buch

@Techmeme@techhub.social
2025-12-23 13:15:44

Google's Nano Banana Pro and OpenAI's ChatGPT Images can make nonconsensual bikini deepfakes from photos of fully clothed women; Reddit bans r/ChatGPTJailbreak (Reece Rogers/Wired)
wired.com/story/google-and-ope

@arXiv_csLG_bot@mastoxiv.page
2025-12-22 11:50:31

Crosslisted article(s) found for cs.LG. arxiv.org/list/cs.LG/new
[2/3]:
- Sharp Structure-Agnostic Lower Bounds for General Functional Estimation
Jikai Jin, Vasilis Syrgkanis
arxiv.org/abs/2512.17341 mastoxiv.page/@arXiv_statML_bo
- Timely Information Updating for Mobile Devices Without and With ML Advice
Yu-Pin Hsu, Yi-Hsuan Tseng
arxiv.org/abs/2512.17381 mastoxiv.page/@arXiv_csNI_bot/
- SWE-Bench : A Framework for the Scalable Generation of Software Engineering Benchmarks from Open...
Wang, Ramalho, Celestino, Pham, Liu, Sinha, Portillo, Osunwa, Maduekwe
arxiv.org/abs/2512.17419 mastoxiv.page/@arXiv_csSE_bot/
- Perfect reconstruction of sparse signals using nonconvexity control and one-step RSB message passing
Xiaosi Gu, Ayaka Sakata, Tomoyuki Obuchi
arxiv.org/abs/2512.17426 mastoxiv.page/@arXiv_statML_bo
- MULTIAQUA: A multimodal maritime dataset and robust training strategies for multimodal semantic s...
Jon Muhovi\v{c}, Janez Per\v{s}
arxiv.org/abs/2512.17450 mastoxiv.page/@arXiv_csCV_bot/
- When Data Quality Issues Collide: A Large-Scale Empirical Study of Co-Occurring Data Quality Issu...
Emmanuel Charleson Dapaah, Jens Grabowski
arxiv.org/abs/2512.17460 mastoxiv.page/@arXiv_csSE_bot/
- Behavioural Effects of Agentic Messaging: A Case Study on a Financial Service Application
Olivier Jeunen, Schaun Wheeler
arxiv.org/abs/2512.17462 mastoxiv.page/@arXiv_csIR_bot/
- Linear Attention for Joint Power Optimization and User-Centric Clustering in Cell-Free Networks
Irched Chafaa, Giacomo Bacci, Luca Sanguinetti
arxiv.org/abs/2512.17466 mastoxiv.page/@arXiv_eessSY_bo
- Translating the Rashomon Effect to Sequential Decision-Making Tasks
Dennis Gross, J{\o}rn Eirik Betten, Helge Spieker
arxiv.org/abs/2512.17470 mastoxiv.page/@arXiv_csAI_bot/
- Alternating Direction Method of Multipliers for Nonlinear Matrix Decompositions
Atharva Awari, Nicolas Gillis, Arnaud Vandaele
arxiv.org/abs/2512.17473 mastoxiv.page/@arXiv_eessSP_bo
- TwinSegNet: A Digital Twin-Enabled Federated Learning Framework for Brain Tumor Analysis
Almustapha A. Wakili, Adamu Hussaini, Abubakar A. Musa, Woosub Jung, Wei Yu
arxiv.org/abs/2512.17488 mastoxiv.page/@arXiv_csCV_bot/
- Resource-efficient medical image classification for edge devices
Mahsa Lavaei, Zahra Abadi, Salar Beigzad, Alireza Maleki
arxiv.org/abs/2512.17515 mastoxiv.page/@arXiv_eessIV_bo
- PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning i...
Brussee, Valkema, Weijer, Doeleman, Schrader, Kers
arxiv.org/abs/2512.17517 mastoxiv.page/@arXiv_csCV_bot/
- HydroGym: A Reinforcement Learning Platform for Fluid Dynamics
Christian Lagemann, et al.
arxiv.org/abs/2512.17534 mastoxiv.page/@arXiv_physicsfl
- When De-noising Hurts: A Systematic Study of Speech Enhancement Effects on Modern Medical ASR Sys...
Chondhekar, Murukuri, Vasani, Goyal, Badami, Rana, SN, Pandia, Katiyar, Jagadeesh, Gulati
arxiv.org/abs/2512.17562 mastoxiv.page/@arXiv_csSD_bot/
- Enabling Disaggregated Multi-Stage MLLM Inference via GPU-Internal Scheduling and Resource Sharing
Lingxiao Zhao, Haoran Zhou, Yuezhi Che, Dazhao Cheng
arxiv.org/abs/2512.17574 mastoxiv.page/@arXiv_csDC_bot/
- SkinGenBench: Generative Model and Preprocessing Effects for Synthetic Dermoscopic Augmentation i...
N. A. Adarsh Pritam, Jeba Shiney O, Sanyam Jain
arxiv.org/abs/2512.17585 mastoxiv.page/@arXiv_eessIV_bo
- MAD-OOD: A Deep Learning Cluster-Driven Framework for an Out-of-Distribution Malware Detection an...
Tosin Ige, Christopher Kiekintveld, Aritran Piplai, Asif Rahman, Olukunle Kolade, Sasidhar Kunapuli
arxiv.org/abs/2512.17594 mastoxiv.page/@arXiv_csCR_bot/
- Confidence-Credibility Aware Weighted Ensembles of Small LLMs Outperform Large LLMs in Emotion De...
Menna Elgabry, Ali Hamdi
arxiv.org/abs/2512.17630 mastoxiv.page/@arXiv_csCL_bot/
- Generative Multi-Objective Bayesian Optimization with Scalable Batch Evaluations for Sample-Effic...
Madhav R. Muthyala, Farshud Sorourifar, Tianhong Tan, You Peng, Joel A. Paulson
arxiv.org/abs/2512.17659 mastoxiv.page/@arXiv_statML_bo
toXiv_bot_toot

@DieGesellschafterinLang@swiss.social
2026-01-31 07:25:46

RIP - Schauspielerin Catherine O’Hara ist mit 71 Jahren gestorben
tagesschau.de/ausland/amerika/

@arXiv_csGT_bot@mastoxiv.page
2025-12-10 07:58:51

Beyond Revenue and Welfare: Counterfactual Analysis of Spectrum Auctions with Application to Canada's 3800MHz Allocation
Sara Jalili Shani, Kris Joseph, Michael B. McNally, James R. Wright
arxiv.org/abs/2512.08106 arxiv.org/pdf/2512.08106 arxiv.org/html/2512.08106
arXiv:2512.08106v1 Announce Type: new
Abstract: Spectrum auctions are the primary mechanism through which governments allocate scarce radio frequencies, with outcomes that shape competition, coverage, and innovation in telecommunications markets. While traditional models of spectrum auctions often rely on strong equilibrium assumptions, we take a more parsimonious approach by modeling bidders as myopic and straightforward: in each round, firms simply demand the bundle that maximizes their utility given current prices. Despite its simplicity, this model proves effective in predicting the outcomes of Canada's 2023 auction of 3800 MHz spectrum licenses. Using detailed round-by-round bidding data, we estimate bidders' valuations through a linear programming framework and validate that our model reproduces key features of the observed allocation and price evolution. We then use these estimated valuations to simulate a counterfactual auction under an alternative mechanism that incentivizes deployment in rural and remote regions, aligning with one of the key objectives set out in the Canadian Telecommunications Act. The results show that the proposed mechanism substantially improves population coverage in underserved areas. These findings demonstrate that a behavioral model with minimal assumptions is sufficient to generate reliable counterfactual predictions, making it a practical tool for policymakers to evaluate how alternative auction designs may influence future outcomes. In particular, our study demonstrates a method for counterfactual mechanism design, providing a framework to evaluate how alternative auction rules could advance policy goals such as equitable deployment across Canada.
toXiv_bot_toot

In several posts, #Grok confirmed that the chatbot had #undressed the recently killed woman, writing in one,
“I generated an AI image altering a photo of #Renee #Good